Activation of melanocortin-1 receptor signaling in melanoma cells impairs T cell infiltration to dampen antitumor immunity

Inhibition of T cell infiltration dampens antitumor immunity and causes resistance to immune checkpoint blockade (ICB) therapy. By in vivo CRISPR screening in B16F10 melanoma in female mice, here we report that loss of melanocortin-1 receptor (MC1R) in melanoma cells activates antitumor T cell response and overcomes resistance to ICB. Depletion of MC1R from another melanocytic melanoma model HCmel1274 also enhances ICB efficacy. By activating the GNAS-PKA axis, MC1R inhibits interferon-gamma induced CXCL9/10/11 transcription, thus impairing T cell infiltration into the tumor microenvironment. In human melanomas, high MC1R expression correlates with reduced CXCL9/10/11 expression, impaired T cell infiltration, and poor patient prognosis. Whereas MC1R activation is restricted to melanoma, GNAS activation by hotspot mutations is observed across diverse cancer types and is associated with reduced CXCL9/10/11 expression. Our study implicates MC1R as a melanoma immunotherapy target and suggests GNAS-PKA signaling as a pan-cancer oncogenic pathway inhibiting antitumor T cell response.

previous screening in the Nature 2017 paper identified multiple members of the same pathway or even the same multi-protein complex.It seems here Mc1r was picked because it has the smallest p-value.Numerous GPCRs can activate cAMP-PKA signaling, and it is not clear whether the screening detected them.It is also surprising that only two known immune invasion regulators were detected.
3. In Figures 1H, 2E, 4F, 4G and S6E, the authors analyzed SKCM TCGA data, with separating groups indicated by MC1R low and high.Such analysis could not draw any sound conclusion because MC1R Red-hair-variant (RHC) significantly impairs the MC1R function, and these variants are frequent in humans.As shown in the previous paper (Robles-Espinoza, C. et al. Nat Commun 7, 12064 (2016)), 8% of individuals had two strong MC1R RHC alleles, and 41% had one in the TCGA SKCM dataset.A sole mRNA expression level could not correctly indicate the function of MC1R.Thus the analysis in Figures 1H, 2E, 4F, and 4G could not support the conclusion.
4. The authors proposed that GNAS-PKA signaling regulates anti-tumor T-cell response.
However, the role of GNAS-cAMP-PKA in tumor cell growth is not thoroughly evaluated.In Figure 1G, the authors found that Mc1r knockdown did not affect tumor growth; the mechanism is unknown.It is well known that cAMP-PKA promotes cancer cell proliferation.
Minor concerns: 1. Figure 1D, the protein level of Mc1r need to be confirmed for knockdown.1E and F, it is clearly shown that here the Mc1r function is dependent on a-MSH treatment.However, it is unknown whether Mc1r is fully activated in vivo without any a-MSH treatment.2A-C, 5C, cell numbers are not enough to determine T cell response.The cells need to be normalized total infiltrating immune cells in the tumors.4. Figure 2D, although MFI reaches stastitcal significance, the difference is marginal and it is not sure whether it can cause biological significance.5.In Figure 3, there is not enough justification to add IFN-gamma in the experiment.

Figure
Previous research showed that cAMP-PKA suppressed PD-L1 expression and enhanced antitumor immunity are not dependent on IFN-gamma.

Reviewer #3 (Remarks to the Author): with expertise in melanoma
In this interesting manuscript, Cui et al. show that the melanocortin receptor-1 (MC1R) promotes B16 murine melanoma growth in immune competent mice via inhibiting expression of CXCL9/10/11.This chemokine reduction is dependent on classical Gs cAMP/PKA/CREB signaling downstream of MC1R and results in an increased immune cell response.Parallel experiments in immune deficient mice show that the tumor promoting effects of MC1R depletion are observed only in immune competent mice.
Overall this is an intriguing and potentially important report.The data are generally wellpresented.However, additional critical controls are needed to validate the findings and interpretation.
The control for this was nontargeting (nonfunctional) gRNA.Experiments should be repeated using a gRNA that is functional and targets a noncritical melanoma gene.The western blot showing that the Cas9 levels in cell lysates are similar is reasonable, but in my view not sufficient to rule out an artifact of the Cas9/KRAB approach.Further, to control for off target effects, it is necessary to rescue the effects of the MC1R depletion with a gRNA resistant MC1R transgene.Similarly, transgene rescue is needed for the Prkaca/Prkabc experiments.
2. It is difficult to determine the significance of the associative human TCGA data without knowing the MC1R genotype.Humans have many common MC1R (hypofunctional) variants, and these are associated with increased risk of melanoma.If the authors' overarching idea is correct, the TCGA data should stratify by MC1R genotype.
3. This paper relies on a single murine cell line model (B16) for all of the melanoma studies.This line lacks the normal oncodriver mutations seen in human melanoma and is of questionable physiologic relevance.Other more modern syngeneic melanoma models are now widely available and at least one of them should be used to validate the findings in B16.
4. The well-established MC1R target MITF is associated with improved clinical outcomes in people (PMID 263171710).This is opposite of what would be predicted based on the authors hypothesis.This discrepancy should be discussed.

Negative data showing lack of tumor growth differences between MC1R expressing vs.
MC1R depleted B16 cells in cells with concurrent CXCL9/10 depletion is reasonable.However, to fully support the conclusion, these data should be complemented by positive data an experiment showing that expression of a gRNA resistant CXCL9/10 transgene rescues the in vivo tumor phenotype.This would then establish the necessity and sufficiency of CXCL9/10 depletion as the major mediator of the MC1R tumor promoting effects.6. GNAS(201C) is apparently associated with increased IFN and GZMB positivity in CD8 TILs.This seems opposite to what would be expected given the protumor effect of the constitutively active GNAS mutant.This should be discussed.7.While I (presumably) understand the rationale for including the small liver and breast studies at the end of the paper, I found them somewhat distracting and unnecessary for this manuscript.They also lack some critical controls, and in my view, the paper would be stronger to use that space to validate the melanoma findings in a different melanoma model.

Reviewer #4 (Remarks to the Author): with expertise in cancer immunology, melanoma
In this manuscript, the authors described a resistant mechanism that melanoma cancer cells express Mc1r to target the IFN-gamma pathway.This leads to the reduction of the expression of CXCL9-11 and therefore the infiltration of T cells.Additional studies indicated that MC1R activates the GNAS-PKA axis to inhibit interferon-gamma (IFNγ) induced CXCL9/10/11 transcription.Together this study reveals MC1R as a potential immunotherapy target that limits antitumor T cell response in melanoma.However, there are many unanswered questions that weaken the claim.

Response to reviewers
We are grateful to all four expert reviewers for their insightful comments.We believe we have addressed their comments to the best of our ability resulting in a significantly strengthened manuscript.
In particular, we have performed multiple control experiments to address concerns with respect to the CRISPR screen and Cas9 system related claims.We also have improved the analysis of the TCGA data by stratifying patients according to their MC1R genotypes.Moreover, we identified an additional mouse melanoma model (HCmel1274) that depends on MC1R to evade antitumor immunity.
In addition to the point-by-point response to the reviewers' comments, we provide the following table to highlight changes in figures.

Previous submission
This submission Changes Figure 1 Figure 1 1H (non-RHC) Figure 2 Figure 2 2E (non-RHC) Figure 3 Figure 3 No change Figure 4 Figure 4 4F (non-RHC), 4G removed Figure 5 New data (a new melanoma model HCmel1274) Figure 5 Figure 6 No change Figure 6 Figure 7 No change Figure S1 Figure S1 S1B-H (new data) Figure S2 Figure S2 S2B (new data) Figure S3 Figure S3 No change Figure S4 Figure S4 No change Figure S5 New data (PD-L1) Figure S5 Figure S6 No change Figure S6 Figure S7 S7A (new data), S7E-F (non-RHC) Figure S7 Figure S8 S8A (new data) Figure S8 Figure S9 S9B, D-H (new data) Figure S9 Figure S10 No change We are very excited by our new results and we look forward to reviewers' feedback.
In the following point-by-point response, reviewer comments are shown in blue, while our responses are shown in black.
Reviewer #1 (Remarks to the Author): with expertise in CRISPR screen, cancer immunology Cui et al identify a PKA mediated signalling module that acts as an inhibitory hub for altering the invasion of anti tumourigenic T cells.They identify these axis through an in vitro/ in vivo screen in which they identify the receptor MC1R that regulates this axis.The inhibition of T cell infiltration is regulated through dampening of CXCL9/10/11 secretion from the tumour cells in response to IFNg.The experiments are generally well performed and the results validated from many different angles.
I always have an issue of using Cas9 or variants of Cas9 in fully immune competent mice as it is well known that Cas9 is highly immunogenic.While this might not affect the results per se, I would like to see some of the validation work of Figure 1 shown in wt also in Cas9 transgenic animals.While the results might be the same, it would be important to test.
We thank the reviewer for pointing out this issue.We performed tumor transplantation experiments in Cas9 transgenic mice as suggested and the results were the same (Figure S1F).
Along the same lines the authors suggest the following, "Because recent studies have revealed the immunogenicity of Cas9 that could influence the antitumor immune response, we monitored dCas9 expression levels by western blotting and found that MC1R depletion did not affect dCas9 expression (Figure 1E)."I don't understand that argument and I also don't understand the rationale for switching to the dCas9-KRAB system to validate the results from the screen.Could the authors please explain and ideally also do one experiment in which the wt Cas9 plus 2 independent MC1R guide RNAs are used and tested in vivo?
We thank the reviewer for pointing this out.The reasons to switch to the dCas9-KRAB system are the following: (1) dCas9-KRAB serves as an orthogonal approach to validate our findings from Cas9-based knockout screening; (2) dCas9-KRAB mediated silencing of Mc1r was efficient and uniform; (3) we were unable to obtain an antibody to validate the knockout efficiency of Mc1r by Cas9 (the widely used anti-mouse MC1R antibody from Santa Cruz is no longer available), whereas the knockdown of Mc1r by dCas9-KRAB could be validated by qPCR.To address the concern raised by the reviewer, we conducted an in vivo experiment using wild-type Cas9 plus two independent MC1R guide RNAs (Figure S1D-E).The results were the same as those obtained from the dCas9-KRAB system (Figure 1E and 1G).
It will also be important to clarify for many experiments (e.g.RNAseq, CXCL9/10 knockout clones, etc) how many Biological replicates were used and how biological replicate is defined as shown e.g. in Figure3.The authors need to make sure that at least 2, ideally 3 biological replicates for some cell lines are being examined.
We apologize for the incomplete definition of biological replicates in our previous submission.Biological replicates in Figure 3 were cells grown in different wells derived from the same stable cell line (either control or MC1R-depleted B16F10).CXCL9/10 knockout clones were two independent clones as judged by distinct indels in CXCL9/10.We now included the definition of biological replicates as part of the figure legends.
Minor points: Statistical analysis of Figure 5d is only done between double ko compared to double NTC.Can they also compare the double to the single KO in that experiment?
Due to the limitation of figure space, we show the full comparisons below.Cxcl9/10/11 levels were significantly higher in double KO in comparison to single KO.
In Figure 5E it would be important to compare the double to the single ko in the in vivo experiments, e.g.Prkaca sgRNA/ Prkacb sgRNA with Prkaca sgRNA/ NTC or Prkacb sgRNA/NTC.
We performed this in vivo experiment as suggested by the reviewer and found that single KO did not slow tumor growth, consistent with the genetic redundancy between Prkaca and Prkacb (Figure S9B).
In Figure 5A expression of GNAS WT and GNAS R201C and in Figure 5F A_CREB should be shown by western analysis.
We now show these results as Figure S8A and Figure S9H.In Figure S8A, we first demonstrated the specificity of our anti-GNAS antibody by comparing control vs. GNAS KO cells.However, expression of cDNA encoding GNAS WT or R201C did not result in higher levels of GNAS comparing to control cells.This is consistent with the fact that RIC-8 is a limiting chaperone for nucleotide-free Gα- Major concerns: 1.The design of the CRISPR screening seems problematic.The authors indicate they used the same method as Manguso, R. et al.Nature 547, 413-418 (2017); however, in the Nature 2017 paper, they used both Tcra−/− and in vitro as controls and treated mice with GVAX or GVAX combined with PD-1 to generate immune-selective pressure on the tumor cells.The authors in this paper only injected the cells into the mice without any treatment; it is doubtful that such a strategy could induce enough immune-selective pressure on the B16 cells.The CRISPR screening in this paper seems to repeat the previous screening with a different library but lower quality.
We agree with the reviewer that the designing of our screening was not as thorough as those presented in Manguso, R. et al.Nature 547, 413-418 (2017).Although we identified known positive regulators of immune evasion (CD47 and PTPN2), we did not attempt to draw conclusions on the pathway mediating immune evasion.Our study was focused on MC1R instead of the entire pathways of immune evasion in the B16F10 melanoma model.We modified the text to reflect the above limitations of our screening.
2. It is not justified how the authors select candidates from the screening result.The previous screening in the Nature 2017 paper identified multiple members of the same pathway or even the same multi-protein complex.It seems here Mc1r was picked because it has the smallest p-value.Numerous GPCRs can activate cAMP-PKA signaling, and it is not clear whether the screening detected them.It is also surprising that only two known immune invasion regulators were detected.
Mc1r was selected because of its smallest P value, high ratio of depletion in vivo, and our interest in studying its biology.By RNA-seq, MC1R is the only highly expressed Gαs-coupled GPCR that can activate cAMP-PKA signaling in B16F10 (Figure S1C).Therefore, no other GPCR should be detected in our screen.As suggested by the reviewer, we did not apply high immune-selective pressure on the tumor cells, therefore we only identified the strongest hits among all possible mediators of immune evasion.4. The authors proposed that GNAS-PKA signaling regulates anti-tumor T-cell response.However, the role of GNAS-cAMP-PKA in tumor cell growth is not thoroughly evaluated.In Figure 1G, the authors found that Mc1r knockdown did not affect tumor growth; the mechanism is unknown.It is well known that cAMP-PKA promotes cancer cell proliferation.In this paper (Cancer Cell, 2020 Mar 16;37(3):324-339.e8), a similar in vivo model was used, and the result showed that cAMP-PKA signaling promotes B16F10 growth in vivo but also enhances immune invasion via PD-L1 regulation.Several papers also show that inhibition of MC1R suppresses cell growth (Onco Targets Ther.2020; 13: 12457-12469., Oncotarget.2016 May 3; 7(18): 26331-26345.).

In
The first publication (Cancer Cell, 2020 Mar 16;37(3):324-339.e8)cited by the reviewer focused on the adenosine receptor A1 (ADORA1).ADORA1 is a Gαi-coupled GPCR, which not only inhibits adenylyl cyclase to dampen cAMP-PKA signaling, but also activates potassium channels called GIRKs (eLife 2019; 8: e44298).In contrast, MC1R is a Gαs-coupled GPCR, which activates adenylyl cyclase to promote cAMP-PKA signaling and does not affect GIRK channels.Therefore, the observation that ADORA1 RNAi reduced cancer cell proliferation does not support the claim that cAMP-PKA promotes cancer cell proliferation.The authors in the publication also showed that ADORA1 RNAi promoted B16F10 immune evasion by upregulating PD-L1 via ATF3.However, whether this regulatory axis was through cAMP-PKA signaling has not been examined (see the dotted line in their graphic abstract).To examine whether MC1R depletion affects PD-L1 levels, we used western blotting and cell surface staining followed by flow cytometry to show that MC1R depletion only modestly reduced cell surface PD-L1 levels by less than 20% (Figure S5).Moreover, If PD-L1 downregulation is indeed the mechanism of MC1R mediated immune evasion, we should not be able to see a synergistic effect between MC1R depletion and anti-PD-1 treatment.Based on the above arguments, this Cancer Cell publication is not inconsistent with our findings and does not comprise the conceptual novelty of our work.
The second publication (Onco Targets Ther.2020; 13: 12457-12469) showed that a fusion protein α-MSH-PE38KDEL consisting of α-MSH and the bacterial toxin PE38KDEL showed high cytotoxicity on MSH receptor-positive melanoma cells.The third publication (Oncotarget.2016 May 3; 7(18): 26331-26345.)showed that expression of Agouti signaling protein (ASIP), which is a natural antagonist of MC1R, in B16F10 reduced lung metastasis in mice but did not affect in vitro cell growth.Based on our findings, this result can be interpreted as inhibition of MC1R by ASIP reduces B16F10 fitness in immunocompetent mice.However, the authors did not propose or experimentally test this hypothesis.In conclusion, these two papers neither support the claim that inhibition of MC1R suppresses cell growth nor comprise the novelty of our work.We thank the reviewer for pointing out these previous studies connecting various GPCRs to PD-L1 expression.As stated in the response to major point #4, our results indicate that MC1R mediated immune evasion is independent of PD-L1.Instead, we provided substantial experimental evidence that MC1R mediated immune evasion dependents on CXCL9/10.Therefore, these prior studies do not comprise the novelty of our study.We agree with the reviewer that our statement that the roles of GPCR in modulating antitumor immunity were unknown was not appropriate.We rephrased this sentence as "Whereas previous studies have revealed the mechanisms by which aberrant GPCR signaling promote cancer cell proliferation, survival, invasion, and metastasis, their roles in modulating antitumor immunity were gaining more attention." The cited study on MITF (J Exp Clin Cancer Res 2021 Mar 31;40(1):117.)showed that MITFdepleted melanoma cells were susceptible to a T cell-independent immune response.The mechanism described in the study is through MITF-induced expression of ADAM10, a key sheddase that cleaves the MICA/B family of ligands for NK cells.In contrast, MC1R-depleted melanomas are susceptible to T cell-dependent immune response.Thus, loss of MITF does not phenocopy loss of MC1R.
We have now included quantitative measurements of PD-L1 expression (Figure S5) which shows that PD-L1 is unlikely to be the downstream effector of MC1R-mediated immune evasion.As elaborated with responses to major points #4 and #5, our results are not inconsistent with these cited studies and the novelty of our work is not compromised by them.As an explanation of tissue specific role of cAMP-PKA pathway, we believe the major determinant is likely the expression and activation of specific GPCRs.In B16F10, MC1R is the only highly expressed Gαs-coupled GPCR (Figure S1C), explaining why we could identify MC1R from our CRISPR screening.The report (Brain Res 2015 Jan 12;1594:27-35) showed that cAMP inhibited lipopolysaccharide (LPS)-induced CXCL10 production in primary murine microglia cells, which is a very different context from melanoma immune evasion.Therefore, we don't think this study in any means limits the novelty and significance of our work.
Minor concerns: 1. Figure 1D, the protein level of Mc1r need to be confirmed for knockdown.
After trying several commercial antibodies, we were unable to obtain an antibody to measure the protein levels of MC1R (The widely used MC1R antibody from Santa Cruz was no longer available).That's one of the reasons why we switched to the dCas9-KRAB system (the knockdown of Mc1r by dCas9-KRAB could be validated by qPCR).Additionally, we used CREB phosphorylation and CRE-luciferase reporter to measure MC1R's biochemical activity.These experiments provided complementary evidence that we have achieved sufficient depletion of MC1R.
2. Figure 1E and F, it is clearly shown that here the Mc1r function is dependent on a-MSH treatment.However, it is unknown whether Mc1r is fully activated in vivo without any a-MSH treatment.
We thank the reviewer for pointing out this issue.To evaluate whether MC1R is fully activated in vivo without any exogenous α-MSH treatment, we transplanted control or MC1R-depleted B16F10 cells harboring the CRE-luciferase reporter into mice, collected tumors on day 10, and performed qPCR of luciferase mRNA.We found that luciferase mRNAs were expressed at significantly lower levels in MC1R-depleted tumors (Figure S7A).This result indicates MC1R is active in vivo in the absence of exogenous α-MSH treatment.
3. Figure 2A-C, 5C, cell numbers are not enough to determine T cell response.The cells need to be normalized total infiltrating immune cells in the tumors.
In addition to cell numbers, we included the normalized data as Figures S2B.2D, although MFI reaches stastitcal significance, the difference is marginal and it is not sure whether it can cause biological significance.

Figure
We agree with the reviewer that the MFI differences were modest.We modified our text to down tune the interpretation of the biological significance of these differences.
5. In Figure 3, there is not enough justification to add IFN-gamma in the experiment.Previous research showed that cAMP-PKA suppressed PD-L1 expression and enhanced anti-tumor immunity are not dependent on IFN-gamma.
As elaborated in our responses to major points #4-6, PD-L1 is unlikely to be the downstream mediator of MC1R-mediated immune evasion.Because IFN-gamma is a master cytokine in orchestrating anti-tumor immune response, we examined the impact of MC1R signaling in IFNgamma response and identified a small subset of IFN-gamma induced genes (including CXCL9/10/11) that were repressed by MC1R signaling.We believe these experiments were logically designed.
Reviewer #3 (Remarks to the Author): with expertise in melanoma In this interesting manuscript, Cui et al. show that the melanocortin receptor-1 (MC1R) promotes B16 murine melanoma growth in immune competent mice via inhibiting expression of CXCL9/10/11.This chemokine reduction is dependent on classical Gs cAMP/PKA/CREB signaling downstream of MC1R and results in an increased immune cell response.Parallel experiments in immune deficient mice show that the tumor promoting effects of MC1R depletion are observed only in immune competent mice.
Overall this is an intriguing and potentially important report.The data are generally wellpresented.However, additional critical controls are needed to validate the findings and interpretation.
1. Most experiments used that dCas9/KRAB repressor protein with gRNA targeting MC1R.The control for this was nontargeting (nonfunctional) gRNA.Experiments should be repeated using a gRNA that is functional and targets a noncritical melanoma gene.The western blot showing that the Cas9 levels in cell lysates are similar is reasonable, but in my view not sufficient to rule out an artifact of the Cas9/KRAB approach.Further, to control for off target effects, it is necessary to rescue the effects of the MC1R depletion with a gRNA resistant MC1R transgene.Similarly, transgene rescue is needed for the Prkaca/Prkabc experiments.
We thank the reviewer for pointing out this issue.As suggested, we performed the following experiments: (1) WT Cas9 with two control sgRNAs (targeting noncritical melanoma genes Rosa26 and H11) and two independent Mc1r-targeting sgRNAs (Figure S1E 2. It is difficult to determine the significance of the associative human TCGA data without knowing the MC1R genotype.Humans have many common MC1R (hypofunctional) variants, and these are associated with increased risk of melanoma.If the authors' overarching idea is correct, the TCGA data should stratify by MC1R genotype.
We thank the reviewer for pointing out this issue.We have now used the MC1R variant annotations from Robles-Espinoza, C. et al.Nat Commun 7, 12064 (2016) to exclude the 8% individuals with two strong MC1R RHC alleles and have redone the bioinformatic analyses.The new set of results support our overarching idea that high MC1R expression in SKCM correlates with poor prognosis, low T cell response, and low CXCL9/10/11 expression.
3. This paper relies on a single murine cell line model (B16) for all of the melanoma studies.This line lacks the normal oncodriver mutations seen in human melanoma and is of questionable physiologic relevance.Other more modern syngeneic melanoma models are now widely available and at least one of them should be used to validate the findings in B16.
We thank the reviewer for this suggestion.In 2020, Glenn Merlino and colleagues reported a panel of four syngeneic melanoma models, which represented a variety of molecular and phenotypic subtypes of human melanomas and exhibited diverse range of responses to immune checkpoint blockade (Nature Medicine 2020, Pubmed ID: 32284588).We found that one of the four models (M3/HCmel1274, representing the melanocytic subtype of melanomas) expressed high levels of MC1R.As shown in Figure 5, depletion of MC1R from this model slowed tumor growth and enhanced response to anti-PD-1 treatment.Together with our previous findings in B16F10, this result suggests that MC1R could be a target for melanomas with melanocytic features.
4. The well-established MC1R target MITF is associated with improved clinical outcomes in people (PMID 263171710).This is opposite of what would be predicted based on the authors hypothesis.This discrepancy should be discussed.
In the literature, the association between MITF with melanoma clinical outcomes has not reached consensus.In the paper cited by the reviewer (Melanoma Res.2015 Dec;25(6):496-502), the authors showed that MITF is associated with improved clinical outcomes in people.However, another highly cited study (Nature 436, 117-122 (2005).https://doi.org/10.1038/nature03664)showed that MITF amplification was more prevalent in malignant melanoma and correlated with decreased overall patient survival.
5. Negative data showing lack of tumor growth differences between MC1R expressing vs. MC1R depleted B16 cells in cells with concurrent CXCL9/10 depletion is reasonable.However, to fully support the conclusion, these data should be complemented by positive data an experiment showing that expression of a gRNA resistant CXCL9/10 transgene rescues the in vivo tumor phenotype.This would then establish the necessity and sufficiency of CXCL9/10 depletion as the major mediator of the MC1R tumor promoting effects.
We appreciate the reviewer's suggestion for this experiment.However, CXCL9/10 are inducible genes regulated by multiple signaling pathways, such as IFNgamma and cAMP-PKA (as shown by us in this study).It is thus technically challenging to design a transgene construct that can faithfully mimic the spatial and temporal regulation of CXCL9/10 expression.
6. GNAS(201C) is apparently associated with increased IFN and GZMB positivity in CD8 TILs.This seems opposite to what would be expected given the protumor effect of the constitutively active GNAS mutant.This should be discussed.
We thank the reviewer for pointing out the mistake we made in the previous manuscript, which has been corrected in the current manuscript.As shown in Figure S8E, GNAS (201C) was associated with decreased IFNgamma and GZMB positivity in CD8 TILs.
7. While I (presumably) understand the rationale for including the small liver and breast studies at the end of the paper, I found them somewhat distracting and unnecessary for this manuscript.They also lack some critical controls, and in my view, the paper would be stronger to use that space to validate the melanoma findings in a different melanoma model.
We thank the reviewer for this suggestion.Because GNAS mutations occur in a variety of tumor types, we feel it is important to examine the effect of GNAS mutations in driving immune evasion in other cancer types.As suggested by the reviewer, we added one entire figure (Figure 5) to validate the B16F10 findings in a different melanoma model HCmel1274.
Reviewer #4 (Remarks to the Author): with expertise in cancer immunology, melanoma In this manuscript, the authors described a resistant mechanism that melanoma cancer cells express Mc1r to target the IFN-gamma pathway.This leads to the reduction of the expression of CXCL9-11 and therefore the infiltration of T cells.Additional studies indicated that MC1R activates the GNAS-PKA axis to inhibit interferon-gamma (IFNγ) induced CXCL9/10/11 transcription.Together this study reveals MC1R as a potential immunotherapy target that limits antitumor T cell response in melanoma.However, there are many unanswered questions that weaken the claim.In the new Figure 5A, by analyzing TCGA and GTEx datasets, we show that high MC1R expression was restricted to a subset of melanomas.We currently do not know what regulates the expression of MC1R, but we think this is an interesting question for future investigation.bystanders, they should not be associated with the loss of specific genes, therefore invisible in the CRISPR screening.

Only B16F10 was tested for Mc1r function in vivo.
We now devoted one entire figure (Figure 5) to validate the function of MC1R in a different melanoma model HCmel1274.
4. How much CXCL9/10 within B16F10 tumor tissues comes from host cells vs cancer cells?Will loss of Mc1r in cancer cells impact intratumoral CXCL9/10?
We thank the reviewer for this question.By qPCR of tumor-derived RNAs, we now demonstrate that loss of MC1R in cancer cells indeed impacted intratumoral CXCL9/10 levels (Figure S7A). Minor: 1. Lack of data about validating the loss of Mc1r protein expression.
After trying several commercial antibodies, we were unable to obtain an antibody to measure the protein levels of MC1R (The widely used MC1R antibody from Santa Cruz was no longer available).That's one of the reasons why we to the dCas9-KRAB system (the knockdown of Mc1r by dCas9-KRAB could be validated by qPCR).Additionally, we used CREB phosphorylation and CRE-luciferase reporter to measure MC1R's biochemical activity.These experiments provided complementary evidence that we have achieved sufficient depletion of MC1R.

Why did Mc1r ablation also increase CD4 T or NK cells? And what about other non-T immune cells in the tumors?
MC1R ablation causes an increase of CXCL9/10/11 production.The receptor of these chemokines, CXCR3, is expressed in CD8+ T cells, CD4+ T cells, and NK cells.As shown in Figure S3B, the number of myeloid cells were not affected by MC1R depletion.
Though the authors had replied to all my questions, I am still not comfort with their response to the advantage of Mc1r-null cells over other targeted cells in vivo in their screening model: once T cells migrate to tumor sites because of increased CXCL9/10, other tumor cells will be recognized and killed by infiltrated T cells at a similar extent.They are not neglected.

Main: 1 .
At present, it is still unclear to how important Mc1r expression contributes to immune resistance in melanoma.How broadly is Mc1r expressed in melanoma or other cancers?And what regulates the expression of Mc1r? 2. Screening out Mc1r as a suppressor for T cell infiltration is a big surprise to me: assuming loss of Mc1r leads to the increase of CXCL9/10/11 and the increase of CD8 T cells, how does Mc1r-negative B16F10 cells have the disadvantage over other tumor cells in vivo?This change of chemokines would impact cancer cells in a whole population, which does not explain its individual disadvantage over its neighboring cancer cells.3.Only B16F10 was tested for Mc1r function in vivo.4. How much CXCL9/10 within B16F10 tumor tissues comes from host cells vs cancer cells?Will loss of Mc1r in cancer cells impact intratumoral CXCL9/10?Minor: 1. Lack of data about validating the loss of Mc1r protein expression.2. Why did Mc1r ablation also increase CD4 T or NK cells?And what about other non-T immune cells in the tumors?Cui et al: Activation of GPCR-GNAS-PKA signaling in cancer cells impairs T cell infiltration to dampen antitumor immunity ); (2) Rescue of the effects of the MC1R depletion with an sgRNA resistant MC1R transgene (Figure S1G-H); (3) Rescue of the effects of Prkaca/Prkabc knockout with an sgRNA resistant PRKACA transgene (Figure S9D-E).

Main: 1 .
At present, it is still unclear to how important Mc1r expression contributes to immune resistance in melanoma.How broadly is Mc1r expressed in melanoma or other cancers?And what regulates the expression of Mc1r?

2.
Screening out Mc1r as a suppressor for T cell infiltration is a big surprise to me: assuming loss of Mc1r leads to the increase of CXCL9/10/11 and the increase of CD8 T cells, how does Mc1rnegative B16F10 cells have the disadvantage over other tumor cells in vivo?This change of chemokines would impact cancer cells in a whole population, which does not explain its individual disadvantage over its neighboring cancer cells.
Figures 1H, 2E, 4F, 4G and S6E, the authors analyzed SKCM TCGA data, with separating groups indicated by MC1R low and high.Such analysis could not draw any sound conclusion because MC1R Red-hair-variant (RHC) significantly impairs the MC1R function, and these variants are frequent in humans.As shown in the previous paper (Robles-Espinoza, C. et al.Nat Commun 7, 12064 (2016)), 8% of individuals had two strong MC1R RHC alleles, and 41% had one in the TCGA SKCM dataset.A sole mRNA expression level could not correctly indicate the function of MC1R.Thus the analysis in Figures 1H, 2E, 4F, and 4G could not support the conclusion.We thank the reviewer for pointing out this issue.We have now used the MC1R variant annotations from Robles-Espinoza, C. et al.Nat Commun 7, 12064 (2016) to exclude the 8% individuals with two strong MC1R RHC alleles and have redone the bioinformatic analyses.The new set of results (Figures 1H, 2E, 4F, S7E, and S7F) support our overarching idea that high MC1R expression in SKCM correlates with poor prognosis, low CXCL9/10/11 expression, and low T cell response.
5. The authors indicate, "Whereas previous studies have revealed the mechanisms by which aberrant GPCR signaling promote cancer cell proliferation, survival, invasion, and metastasis, their roles in modulating antitumor immunity were unknown."However, the role of GPCR in antitumor immunity is well-studied.Examples: ADORA1 inhibition promotes tumor immune evasion